Image processing apparatus and method

ABSTRACT

By smoothing a full-color image, staircasing of characters even in a gradation image is removed. An area to be smoothed is detected from image data having a plurality of color components, and image data included in the detected area is smoothed in units of color components.  
     Image data which places an importance on resolution is smoothed by increasing the resolution to reproduce smooth characters and figures. Image data which places an importance on gradation characteristic is output without increasing the resolution, thus attaining high-gradation recording. A character or figure is detected from bitmap image data input from external equipment, and is smoothed. In correspondence with the density of the smoothed image data, the pulse width is switched, thereby changing the resolution of image data.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to an image processing apparatusand method and, more particularly, to an image processing apparatus andmethod, which extract an image feature portion from color image dataelectrically read based on an original image or color image data createdby a computer, and process color image data to be output to, e.g., aprinter on the basis of the extraction result.

[0003] The present invention relates to an image processing apparatusand method and, more particularly, to an image processing apparatus andmethod, which smoothes a bit map image data showing character and figureoutput by external equipment.

[0004] 2. Description of Related Art

[0005] In recent years, a color printer apparatus which obtains colorimages by outputting digitally processed color image data, and a colorimage printing system such as a so-called digital color copying machine,and the like, which color-separates and electrically reads a colororiginal image, and obtains a copy of a color image by printing out theread color image data onto a recording paper sheet have evolvedremarkably. As such apparatuses prevail, requirements for image qualityof color images are becoming stricter, and especially, requirements forprinting black characters and lines more clearly and sharply arebecoming stricter. More specifically, when a black original image iscolor-separated, yellow; magenta, cyan, and black signals are generatedas those for reproducing black. When printing is done directly based onthe obtained signals, since black is reproduced by superposing thesefour colors, a black thin line produces smear due to slightmisregistration among the colors. As a result, black does not appearblack or is blurred, thus considerably deteriorating the print quality.

[0006] On the other hand, in one method, information associated withblack, color information associated with colors, and feature data of thespatial frequencies of thin lines, dot patterns, and the like areextracted from an image signal representing an image to be processed todetect, e.g., areas for black characters, color characters, and thelike, and to also detect areas for a halftone image, dot pattern image,and the like, and image processing suitable for each detected area isdone so as to express, e.g., black characters using black alone. Also,in another method proposed, a plurality of different thicknesses ofcharacters and lines can be discriminated, and the color amount of blackis adjusted or character and dot pattern edges are separately detectedin accordance with the thicknesses of characters to execute differentimage processing operations for character edges in a dotpattern/halftone image or white background, thus attaining smooth blackcharacter processing. However, even after image area separation, since aprinter having a resolution of about 400 dpi has a dot spacing of 63.5microns, character and figure edges formed by dots look shaggy with thevisual sense of a human being, that can distinguish up to about 20microns, and the print quality is not so high.

[0007] In order to improve the print quality, a system shown in FIG. 32is known. In this conventional system, a page layout document for DTP,wordprocessing or graphic document, or the like is created using a hostcomputer 1310, and is printed out by a color printer (laser beamprinter) via a raster imageprocessor 1313. Reference numeral 1311denotes an application program running on the host computer 1310, andfor example, wordprocessing software such as “Word” (trademark)available from Microsoft Corporation, page layout software such asPageMarker (trademark) available from Adobe Corporation, and the like,are popularly used. A digital document created by such software is sentto a printer driver 1312 via an operating system (OS; not shown) of thecomputer. This digital document is normally a set of command data thatrepresent figures, characters, and the like in one page, and thesecommands are sent to the printer driver 1312. The commands are expressedas a language system called a PDL (page description language), and GDI(trademark), PS (PostScript: trademark), and the like are typical PDLs.The printer driver 1312 transfers PDL commands output from theapplication 1311 to a rasterizer 1314 in the raster image processor1313. The rasterizer 1314 maps characters, figures, and the likeexpressed by the PDL commands to an actual two-dimensional bitmap imageto be printed out. The rasterizer 1314 uses a frame as a two-dimensionalplane, and forms the bitmap image over the entire frame byone-dimensionally repetitively scanning (rasterizing) in units of lines.The bitmap image mapped by the rasterizer 1314 is temporarily stored inan image memory 1315.

[0008] A document image displayed on the host computer 1310 is sent asPDL commands to the rasterizer 1314 via the printer driver 1312, and therasterizer 1314 maps a two-dimensional bitmap image onto the imagememory 1315. The mapped image data is sent to a color printer 1318. Thecolor printer 1318 mounts a known electrophotographic image forming unit1319, which prints out the image data by forming a visible image on arecording paper sheet. The image data in the image memory 1315 istransferred in synchronism with sync signals and clock signals requiredfor operating the image forming unit 1319, or a specific color componentsignal, its request signal, and the like.

[0009] Smoothing is known as a technique for improving the print qualityby removing shagginess or staircasing of character and line image edges.However, no conventional method of satisfactorily smoothing multi-color,multivalued image data is available.

[0010] When full-color image data transferred from an external equipmentincludes both character and picture data, its image quality can befurther improved using an adaptive processing circuit which is mountedon, e.g., a color copying machine or the like. However, character areascannot always be detected 100% by image area separation, and may beerroneously detected in a natural image area, resulting in poorreliability.

[0011] When characters and figures created by a personal computer areprinted out as monochrome images using a 400-dpi printer, for example,if an image described in a page description language is rasterized,staircasing inevitably remains. In case of a color printout, since imagedata that places an importance on gradation may be simultaneouslytransferred, if the resolution of such image data is also increased bysmoothing in the same manner as in other areas, the image qualitydeteriorates.

SUMMARY OF THE INVENTION

[0012] It is an object of the present invention to provide an imageprocessing apparatus and method, which can eliminate staircasing incolor characters and line images even in a gradation image by smoothinga multi-color, multi-valued image, and can improve the image quality.

[0013] In order to achieve the above object, an image processingapparatus according to the present invention comprises the followingarrangement.

[0014] That is, an image processing apparatus comprises:

[0015] input means for inputting multi-valued image data having aplurality of color components;

[0016] detection means for detecting an area to be smoothed from themulti-valued image data having the plurality of color components; and

[0017] smoothing means for smoothing multi-valued image data included inthe area detected by the detection means in units of color components.

[0018] In order to achieve the above object, an image processing methodaccording to the present invention has the following features.

[0019] That is, an image processing method comprises:

[0020] the input step of inputting multi-valued image data having aplurality of color components;

[0021] the detection step of detecting an area to be smoothed from themulti-valued image data having the plurality of color components; and

[0022] the smoothing step of smoothing multi-valued image data includedin the area detected in the detection step in units of color components.

[0023] It is another object of the present invention to provide an imageprocessing apparatus and method, which can further improve image qualityby executing adaptive processing of a full-color image input from anexternal equipment using image separation information and attribute mapinformation.

[0024] In order to solve the above-mentioned problems and to achieve theobject, an image processing apparatus according to the present inventioncomprises the following arrangement.

[0025] That is, an image processing apparatus comprises:

[0026] input means for inputting a command that represents an image;

[0027] bitmap data generation means for generating bitmap data on thebasis of the command that represents the image; and

[0028] attribute generation means for generating attribute informationon the basis of an attribute of an object that forms an image, and thebitmap data.

[0029] An image processing method according to the present invention hasthe following features.

[0030] That is, an image processing method comprises:

[0031] the input step of inputting a command that represents an image;

[0032] the bitmap data generation step of generating bitmap data on thebasis of the command that represents the image; and

[0033] the attribute generation step of generating attribute informationon the basis of an attribute of an object that forms an image, and thebitmap data.

[0034] It is still another object of the present invention to provide animage processing apparatus and method, which can reproduce smoothcharacters and figures by increasing their resolution by smoothing theiredges, and can output image data, which places an importance ongradation, without increasing its resolution, even when such image datais transferred.

[0035] In order to solve the above-mentioned problems and to achieve theabove object, an image processing apparatus according to the presentinvention comprises the following arrangement.

[0036] That is, an image processing apparatus comprises:

[0037] input means for inputting image data having a plurality of colorcomponents, obtained by color-separating an image;

[0038] detection means for detecting an area to be smoothed from theimage data having the plurality of color components;

[0039] smoothing means for smoothing the image data having the pluralityof color components included in the area detected by the detectionmeans;

[0040] output means for outputting a recording signal of a predeterminedresolution on the basis of the smoothed image data; and

[0041] switching means for switching an output resolution of the outputmeans.

[0042] An image processing method according to the present invention hasthe following features.

[0043] That is, an image processing method comprises:

[0044] the input step of inputting image data having a plurality ofcolor components, obtained by color-separating an image;

[0045] the detection step of detecting an area to be smoothed from theimage data having the plurality of color components;

[0046] the smoothing step of smoothing the image data having theplurality of color components included in the area detected in thedetection step;

[0047] the output step of outputting a recording signal of apredetermined resolution on the basis of the smoothed image data; and

[0048] the switching step of switching an output resolution of theoutput step in correspondence with a characteristic of the smoothedimage data.

[0049] Other objects and advantages besides those discussed above shallbe apparent to those skilled in the art from the description ofpreferred embodiments of the invention which follows. In thedescription, reference is made to accompanying drawings, which form apart thereof, and which illustrate an example of the invention. Suchexample, however, is not exhaustive of the various embodiments of theinvention, and therefore reference is made to the claims which followthe description for determining the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0050]FIG. 1 is a view showing the outer appearance of an apparatusaccording to the first embodiment of the present invention;

[0051]FIG. 2A is a perspective view showing a CCD 210 used in theapparatus shown in FIG. 1;

[0052]FIG. 2B is an enlarged view of a portion X shown in FIG. 2A;

[0053]FIG. 2C is a sectional view taken along a line A-A in FIG. 2A;

[0054]FIG. 3 is a block diagram showing the detailed arrangement of animage signal processing unit 209 shown in FIG. 1;

[0055]FIG. 4 is a block diagram showing the detailed arrangement of adensity-luminance conversion unit 102 shown in FIG. 3;

[0056]FIG. 5 is a block diagram showing the detailed arrangement of aluminance calculation circuit 301 shown in FIG. 4;

[0057]FIG. 6 is a view for explaining the processing in an edge mindirection detector 302 shown in FIG. 4;

[0058]FIGS. 7A and 7B are views showing image data and an edge detectionsignal in luminance data Y;

[0059]FIG. 8 is a block diagram showing the detailed arrangement of asaturation determination unit 109 shown in FIG. 3;

[0060]FIG. 9 is a graph showing the characteristics of a saturationsignal Cr in the saturation determination unit 109 shown in FIG. 3;

[0061]FIG. 10 is a block diagram showing the detailed arrangement of acharacter thickness discrimination circuit 110;

[0062]FIG. 11 is a block diagram showing the detailed arrangement of acharacter/halftone detector 903 shown in FIG. 10;

[0063]FIG. 12 is a block diagram showing the detailed arrangement of adot pattern area detector 904 shown in FIG. 10;

[0064]FIGS. 13A to 13D show the edge direction detection rules in anedge direction detector 2044 shown in FIG. 12;

[0065]FIG. 14 shows values of pixels around the pixel of interest, i.e.,values output from the edge direction detector 2044;

[0066]FIGS. 15A to 15I show patterns of a window set by a counter 2049shown in FIG. 12;

[0067]FIG. 16 is a block diagram showing the detailed arrangement of anarea size determination circuit 906 shown in FIG. 10;

[0068]FIG. 17 is an explanatory view of the procedure for determining anoutput signal PICT_FH;

[0069]FIG. 18 shows the encode rule of an encoder 2083;

[0070]FIG. 19 is a diagram showing the algorithm for character detectionin a dot pattern/halftone image;

[0071]FIG. 20 is a diagram showing processes until an FCH signal isgenerated;

[0072]FIG. 21 is a block diagram showing the detailed arrangement of asmoothing circuit 104 shown in FIG. 3;

[0073]FIG. 22 shows an example of an actually input image signal;

[0074]FIG. 23 shows the smoothing result of the image signal shown inFIG. 22;

[0075]FIG. 24 is a block diagram showing the detailed arrangement of apattern matching circuit 1002 shown in FIG. 21;

[0076]FIG. 25 is a view for explaining an example of smoothingrasterized density data 255 in a line having one pixel width;

[0077]FIG. 26 is a view for explaining an example of interpolation in asmoothing processing circuit 1003 shown in FIG. 21;

[0078]FIG. 27 is a block diagram showing an image processing systemaccording to the second embodiment of the present invention;

[0079]FIG. 28 is a view showing image data mapped on an image memory1315 in FIG. 27;

[0080]FIGS. 29A to 29E are enlarged views of portion A in FIG. 28;

[0081]FIGS. 30A to 30E are enlarged views of portion B in FIG. 28;

[0082]FIG. 31 is a block diagram of an image processor 1317 shown inFIG. 27;

[0083]FIG. 32 is a block diagram showing a conventional image processingsystem;

[0084]FIG. 33 is a timing chart showing the control for densityreproduction of a printer according to the third embodiment of thepresent invention;

[0085]FIG. 34 is a block diagram showing the detailed arrangement of theimage processing unit 209 shown in FIG. 1;

[0086]FIGS. 35A and 35B are views for explaining the algorithm forextracting the feature of a dot pattern over the entire matrix area anddiscriminating whether or not the dot pattern is to be smoothed; and

[0087] FIGS. 36 to 38 show examples of memory maps when the imageprocessing method of the present invention is stored in a storagemedium.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0088] The preferred embodiments of the present invention will bedescribed in detail hereinafter with reference to the accompanyingdrawings.

[0089] [First Embodiment]

[0090]FIG. 1 is a view showing the outer appearance of an apparatusaccording to the first embodiment of the present invention.

[0091] In FIG. 1, an image scanner module 201 reads an original image,and performs digital signal processing of the read image. A printermodule 200 prints out a full-color image corresponding to the originalimage read by the image scanner module 201 onto a paper sheet.

[0092] In the image scanner module 201, light emitted by a halogen lamp205 and to be irradiated onto an original 204 on an original table glass(to be referred to as a platen hereinafter) 203 is irradiated onto anoriginal pressing plate 202. Light reflected by the original is guidedby mirrors 206 and 207, and is imaged on a 3-line sensor (to be referredto as a CCD hereinafter) 210 via a lens 208. The lens 208 has aninfrared cut filter 231.

[0093] The CCD 210 color-separates optical information obtained from theoriginal, reads the red (R), green (G), and blue (B) components offull-color information, and sends them to a signal processing unit 209.

[0094] Each of color component read sensor arrays of the CCD 210 iscomprised of 5,000 pixels. With these pixels, the CCD 210 reads thewidthwise direction (297 mm) of an A3-size original as a maximum one ofthose placed on the platen 203 at a resolution of 400 dpi.

[0095] Note that a first sub-scanning unit (205 and 206) scans theentire original surface when it mechanically moves in a direction (to bereferred to as a sub-scanning direction hereinafter) perpendicular to anelectrical scanning direction (to be referred to as a main scanningdirection hereinafter) of the CCD at a velocity v, and a second scanningunit (207) scans the entire original surface when it mechanically movesin the direction perpendicular to the electrical scanning direction ofthe CCD at a velocity 0.5 v.

[0096] A standard white plate 211 is used for generating correction datafor data read by R, G, and B sensors 210-1 to 210-3.

[0097] The standard white plate 211 exhibits nearly uniform reflectioncharacteristics for visible light, and is white in visible range. Usingthis standard white plate 211, output data from the sensors 210-1 to210-3 in visible range are corrected.

[0098] The image signal processing unit 209 processes the read opticalinformation as electrical signals to separate it into magenta (M), cyan(C), yellow (Y), and black (BK) components, and sends them to theprinter module 200. Since one of M, C, Y, and BK components is sent tothe printer module 200 per original scan of the image scanner module201, a single printout is completed by a total of four original scans(for four colors).

[0099] An image signal, i.e., one of M, C, Y, and BK color componentssent from the image scanner module 201 is supplied to a laser driver212. The laser driver 212 modulates and drives a semiconductor laser 213in correspondence with the image signal. A laser beam scans the surfaceof a photosensitive drum 217 via a polygonal mirror 214, f-θ lens 215,and mirror 216.

[0100] Reference numerals 219 to 222 denote magenta, cyan, yellow, andblack developers. These four developers alternately contact thephotosensitive drum to develop an electrostatic latent image of one ofthe M, C, Y, and BK color components formed on the photosensitive drum217 with corresponding toner.

[0101] A paper sheet fed from a paper cassette 224 or 225 is woundaround a transfer drum 223, which transfers the toner image developed onthe photosensitive drum 217 onto the paper sheet.

[0102] With the above-mentioned procedure, a total of four color imagesare frame-sequentially transferred onto the paper sheet in units of M,C, Y, and BK color components, and the paper sheet is then exhausted viaa fixing unit 226.

[0103] A summary of the operation of the apparatus has been given.

[0104] The image scanner module 201 will be described in detail below.

[0105]FIG. 2A shows the outer appearance of the CCD 210 used in theapparatus shown in FIG. 1.

[0106] In FIG. 2A, reference numeral 210-1 denotes a light-receivingelement array for reading red light (R); 210-2, a light-receivingelement array for reading green light (G); and 210-3, a light-receivingelement array for reading blue light (B).

[0107] The R, G, and B light-receiving element arrays 210-1 to 210-3have 10 μm×10 μm openings in the main scanning and sub-scanningdirections, as shown in FIG. 2B.

[0108] These three light-receiving element arrays having differentoptical characteristics are monolithically formed on a single siliconchip so that the R, G, and B sensor arrays are disposed parallel to eachother to read an identical line on an original.

[0109] Using the CCD with this arrangement, a common optical system suchas a lens and the like can be used upon reading separated colors.

[0110] In this way, optical adjustment in units of R, G, and B colorcomponents can be simplified.

[0111]FIG. 2B is an enlarged view of a portion X shown in FIG. 2A, andFIG. 2C is a sectional view taken along a line A-A in FIG. 2A.

[0112] In FIG. 2C, the photosensor 210-1 for reading red light, and thephotosensors 210-2 and 210-3 for reading visible information of greenand read are formed on a silicon substrate 210-5.

[0113] An R filter 210-7 for transmitting the red (R) wavelengthcomponent of visible light is set on the red photosensor 210-1.Similarly, G and B filters 210-8 and 210-9 for respectively transmittingthe green (G) and blue (B) wavelength components are set on the greenand blue photosensors 210-2 and 210-3. Reference numeral 210-6 denotes aplanarization layer formed of a transparent organic film.

[0114] In FIG. 2B, each of the photosensors 210-1 to 210-3 has a lengthof 10 μm per pixel in the main scanning direction. Each of thephotosensors 210-1 to 210-3 has 5,000 pixels in the main scanningdirection to be able to read the widthwise direction (297 mm) of anA3-size original at a resolution of 400 dpi.

[0115] The line spacing between adjacent R, G, and B photosensors 210-1to 210-3 is 80 μm, i.e., the adjacent photosensors are spaced by 8 lineswhich correspond to 400 dpi sub-scanning resolution.

[0116] The density reproduction method of the printer will be explainedbelow.

[0117] This embodiment uses so-called pulse width modulation (PWM) fordensity reproduction of the printer, and controls the ON time of thelaser 213 in correspondence with an image density signal. With thiscontrol, an electrostatic latent image with a potential corresponding tothe ON time of the laser is formed on the photosensitive drum 217.Density reproduction is attained by developing the electrostatic latentimage with toner corresponding in amount to the potential of the latentimage using the developers 219 to 222.

[0118]FIG. 3 is a block diagram showing the detailed arrangement of theimage signal processing unit 209.

[0119] In FIG. 3, image signals Y, M, C, and K output from an externalequipment 101 such as a computer or the like are sequentiallytransferred in units of scanning frames in a printer unit 106, and adensity-luminance converter 102 converts density signals Y, M, C, and Kinto luminance signals R, G, and B using a look-up table ROM in units ofcolors.

[0120] A luminance-density converter 103 converts three primary colorsignals R, G, and B transferred from the CCD 210 or the externalequipment into density signals Y, M, C, and K, and frame-sequentiallyoutputs the density signals to have a predetermined bit width (8 bits).

[0121] A smoothing circuit 104 generates data having a resolution twicethe reading resolution in accordance with a result from an image areaseparation unit 107 and an area signal supplied from a console 112 orthe external equipment 101, as will be described later. A γ table 105converts the resolution-converted density data in correspondence withthe gradation reproduction characteristics of the printer. The processedimage signals M, C, Y, and K and an sen signal as a switching signalbetween 400 dpi/800 dpi are sent to the laser driver, and the printerunit 106 performs density recording by PWM.

[0122] The image area separation unit 107 has an edge detector 108,saturation determination unit 109, thickness discrimination circuit 110,and look-up table (LUT) 111. The edge detector 108 generates an edgesignal edge from image signals R, G, and B output from thedensity-luminance converter 102, and outputs it to the LUT 111. Thesaturation determination unit 109 generates a saturation signal col fromimage signals R, G, and B output from the density-luminance converter102, and outputs it to the LUT 111. The thickness discrimination circuit110 generates a thickness signal zone from image signals R, G, and Boutput from the density-luminance converter 102, and outputs it to theLUT 111.

[0123] A black character/black line image detection method will beexplained below.

[0124] <Operation of Edge Detector 108 in FIG. 3>

[0125] The density-luminance converted signals R, G, and B are input tothe edge detector 108, and a luminance calculation circuit 301 shown inFIG. 1 calculates a luminance signal Y given by:

Y=0.25R+0.5G+0.25B  (1)

[0126]FIG. 5 shows the detailed arrangement of the luminance calculationcircuit 301. In FIG. 5, multipliers 401, 402, and 403 respectivelymultiply input color component signals R, G, and B by coefficients“0.25”, “0.5”, and “0.25”, and adders 404 and 405 add the products toobtain the luminance signal Y given by equation (1).

[0127] The luminance signal Y input to an edge min direction detector302 is expanded to three lines delayed by one line by FIFOs 501 and 502shown in FIG. 6, and these signals are filtered by so-called Laplacianfilters 503 to 506 to obtain a direction in which an absolute value a ofthe edge amount as the output from each filter assumes a minimum value.The obtained direction is determined as an edge min direction.

[0128] An edge min direction smoothing unit 303 smoothes data in theedge min direction obtained by the edge min direction detector 302. Withthis smoothing, edge components in only the direction corresponding tothe largest edge component can be preserved, and those in otherdirections can be smoothed. More specifically, the feature of a dotpattern component which has large edge components in a plurality ofdirections decreases since the edge components are smoothed. On theother hand, the feature of a character/thin line component which has anedge component in only one direction can be preserved. By repeating thisprocessing as needed, line and dot pattern components can be separatedmore effectively, and any character component present in a dot pattern,which cannot be detected by edge detection methods used to date, can bedetected.

[0129] After that, in an edge detector 304, the output from thesmoothing unit 303 is filtered by the above-mentioned Laplacian filtersto remove data equal to or smaller than the absolute value a of the edgeamount, and to output only data larger than a as “1”.

[0130]FIGS. 7A and 7B show image data and an edge detection signal inluminance data Y.

[0131] Furthermore, the output signal “edge” (3 bits) from the edgedetector 108 shown in FIG. 3 expresses the discrimination signal by fivecodes, i.e., signals expanded by 7×7, 5×5, and 3×3 block sizes, theabsence of expansion, and the absence of edge. Note that signalexpansion means ORing the signal values of all the pixels in a block.

[0132] <Operation of Saturation Determination Unit 109 in FIG. 3>

[0133]FIG. 8 shows the detailed arrangement of the saturationdetermination unit 109.

[0134] As shown in FIG. 8, maximum and minimum value detectors 701 and702 respectively extract maximum and minimum values MAX(r, g, b) andMIN(r, g, b) from color component signals R, G, and B, and a subtracter703 calculates a difference ΔC between these maximum and minimum values.An LUT (look-up table) 704 converts the difference AC in accordance withthe characteristics shown in FIG. 9, thus generating a saturation signalCr. In FIG. 9, as ΔC is closer to “0”, saturation is lower (closer toachromatic color); as ΔC is larger, the color is closer to chromaticcolor. Hence, from the characteristics shown in FIG. 9, Cr assumes alarger value as the color is closer to achromatic color, and approaches“0” as the color is closer to chromatic color. The signal Cr changes atthe rate shown in FIG. 9. Note that the output signal col shown in FIG.3 expresses color, black, intermediate (color between the color andblack), and white using 2-bit codes.

[0135] <Operation of Thickness Discrimination Circuit 110 in FIG. 3>

[0136]FIG. 10 shows the detailed arrangement of the character thicknessdiscrimination circuit 110.

[0137] In FIG. 10, color component signals R, G, and B are input to aminimum value detection circuit 901. The minimum value detection circuit901 detects a minimum value MINR, MING, or MINB of the input R, G, and Bsignals. The value MINR, MING, or MINB is input to an average valuedetector 902 to calculate an average value AVE5 of MINR, MING, or MINBin 5 pixels×5 pixels around the pixel of interest, and an average valueAVE3 of MINR, MING, or MINB in 3 pixels×3 pixels around the pixel ofinterest.

[0138] The values AVE5 and AVE3 are input to a character/halftonedetector 903. The character/halftone detector 903 detects the changeamount between the density of the pixel of interest and the averagedensity of the pixel of interest and its surrounding pixels in units ofpixels, thus discriminating if the pixel of interest is a portion of acharacter or halftone area.

[0139]FIG. 11 shows the detailed arrangement of the character/halftonedetector 903 shown in FIG. 10. In FIG. 11, in the character/halftonedetector 903, a proper offset value OFST1 is added to AVE5, and the sumis compared with AVE3 in a comparator 2031. Also, the sum is comparedwith a proper limit value LIM1 in a comparator 2032. The output valuesfrom the two comparators are input to an OR gate 2033, an output signalBINGRA of which goes High when:

AVE5+OFST1>AVE3  (2)

[0140] or

AVE5+OFST1>LIM1  (3)

[0141] That is, when this circuit detects that a change in density ispresent near the pixel of interest (character edge portion) or pixelsnear the pixel of interest have a density equal to or larger than agiven value (inside a character and a halftone portion), thecharacter/halftone signal BINGRA goes High.

[0142] Subsequently, a dot pattern area detector 904 detects a dotpattern area. FIG. 12 shows the detailed arrangement of the dot patternarea detector 904 in FIG. 10. In FIG. 12, a proper offset value OFST2 isadded to the value MINR, MING, or MINB detected by the minimum valuedetection circuit 901, and the sum is compared with AVE5 in a comparator2041. Also, a comparator 2042 compares MINR, MING, or MINB with a properlimit value LIM2. The output values from the two comparators are inputto an OR gate 2043, an output signal BINAMI of which goes High when:

MIN(R, G, B)+OFST2>AVE5  (4)

[0143] or

MIN(R, G, B)+OFST2>LIM2  (5)

[0144] Using the signal BINAMI, an edge direction detector 2044 detectsthe edge direction in units of pixels. FIGS. 13A to 13D show the edgedirection detection rules in the edge direction detector 2044. In FIGS.13A to 13D, when eight pixels around the pixel of interest satisfy oneof conditions shown in FIGS. 13A to 13D, one of bits 0 to 3 of an edgedirection signal DIRAMI is set High.

[0145] Furthermore, an opposing edge detector 2045 detects opposingedges in an area of 5 pixels×5 pixels that surround the pixel ofinterest. In a coordinate system which includes the signal DIRAMI of thepixel of interest as pixel A33 shown in FIG. 14, the opposing edgedetection rules are as follows:

[0146] (1) bit 0 of one of pixels A11, A21, A31, A41, A51, A22, A32,A42, and A33 is High, and bit 1 of one of pixels A33, A24, A34, A44,A15, A25, A35, A45, and A55 is High;

[0147] (2) bit 1 of one of pixels A11, A21, A31, A41, A51, A22, A32,A42, and A33 is High, and bit 0 of one of pixels A33, A24, A34, A44,A15, A25, A35, A45, and A55 is High;

[0148] (3) bit 2 of one of pixels A11, A12, A13, A14, A15, A22, A23,A24, and A33 is High, and bit 3 of one of pixels A33, A42, A43, A44,A51, A52, A53, A54, and A55 is High; and

[0149] (4) bit 3 of one of pixels A11, A12, A13, A14, A15, A22, A23,A24, and A33 is High, and bit 2 of one of pixels A33, A42, A43, A44,A51, A52, A53, A54, and A55 is High.

[0150] When one of conditions (1) to (4) above is satisfied, a signalEAAMI goes High.

[0151] When opposing edges are detected by the opposing edge detector2045, the opposing edge signal EAAMI goes High.

[0152] Then, an expansion circuit 2046 shown in FIG. 12 performsexpansion of 3 pixels×4 pixels for the signal EAAMI, and if a pixel withHigh EAAMI is included in 3 pixels×4 pixels around the pixel ofinterest, the signal EAAMI of the pixel of interest is rewritten toHigh. Furthermore, using a contraction circuit 2047 and expansioncircuit 2048, an isolated detection result in an area of 5 pixels×5pixels is removed to obtain an output signal EBAMI. Note that thecontraction circuit 2047 outputs High only when all the input signalsare High.

[0153] A counter 2049 counts the number of pixels corresponding to Highoutput signals EBAMI from the expansion circuit 2048 within a windowhaving an appropriate size. In this embodiment, an area of 5 pixels×64pixels including the pixel of interest is referred to. FIGS. 15A to 15Ishow window patterns. In FIGS. 15A to 15I, sample points in a window arenine points at 4-pixel intervals in the main scanning direction, andfive lines in the sub-scanning direction, i.e., a total of 45 points. Bymoving this window in the main scanning direction for one pixel ofinterest, nine windows shown in FIGS. 15A to 15I are prepared. That is,the area of 5 pixels×64 pixels having the pixel of interest as thecenter is referred to. In the individual windows, the number of Highsignals EBAMI is counted, and when the number of High signals EBAMIexceeds an appropriate threshold value, a dot pattern area signal AMIgoes High.

[0154] As described above, with the processing in the dot pattern areadetector 904 shown in FIG. 10, a dot pattern image detected as a set ofisolated points by the above-mentioned signal BINGRA can be detected asan area signal.

[0155] The character/halftone area signal BINGRA and dot pattern areasignal AMI detected by the above-mentioned processing are ORed by anORgate 905, thus generating a binary signal PICT of the input image.

[0156] Then, the signal PICT is input to an area size determinationcircuit 906 to discriminate the area size of the binary signal.

[0157]FIG. 16 shows the detailed arrangement of the area sizedetermination circuit 906 shown in FIG. 10. As shown in FIG. 16, thearea size determination circuit 906 includes a plurality of pairs ofcontraction circuits 2081 and expansion circuits 2082, which havedifferent area sizes to refer to. The signal PICT is line-delayed incorrespondence with the sizes of the contraction circuits, and is theninput to the contraction circuits 2081. In this embodiment, sevendifferent contraction circuits from 23 pixels×23 pixels to 35 pixels×35pixels are prepared. Signals output from the contraction circuits 2081are line-delayed, and are then input to the expansion circuits 2082. Inthis embodiment, seven different expansion circuits from 27 pixels×27pixels to 39 pixels×to 39 pixels are prepared in correspondence with theoutputs from the contraction circuits shown in FIG. 16, and outputsignals PICT_FH from the respective expansion circuits are obtained.

[0158] When the pixel of interest is a portion of a character, theoutput signal PICT_FH is determined by the thickness of that character.

[0159]FIG. 17 is an explanatory view of the processes for determiningthe output signal PICT_FH. As shown in FIG. 17, for example, when thesignal PICT has a width of 26 pixels and is present in a band pattern,if it undergoes contraction with a size larger than 27 pixels×27 pixels,the output becomes all “0”s; if the signal PICT undergoes contractionwith a size smaller than 25 pixels×25 pixels and then undergoesexpansion with the corresponding size, a band-like output signal PICT_FHhaving a width of 30 pixels is obtained. When these output signalsPICT_FH are input to an encoder 2083 shown in FIG. 16, an image areasignal ZONE_P to which the pixel of interest belongs is obtained. FIG.18 shows the encode rule of the encoder 2083. With this processing, apicture image or dot pattern image having High signals PICT over a broadarea is defined as area 7 (maximum value), and a character or line imagesmaller (thinner) than the area size maximum value is defined as amulti-valued image area corresponding to its size (thickness). In thisembodiment, the signal ZONE consists of 3 bits to express the thicknessof a character in eight levels. The thinnest character is indicated by“0”, and the thickest character (including an area other than acharacter) is indicated by “7”. FIG. 19 shows the algorithm forcharacter detection in a dot pattern/halftone image. The above-mentionedsignal PICT is expanded using a 5×5 block in a process 2111. With thisprocessing, a dot pattern area which is often detected as an imperfectarea is corrected. Then, the output signal from the process 2111 iscontracted using a 11×11 blocks in a process 2112. A signal FCH obtainedby such processing is contracted by three pixels as compared to thesignal PICT. FIG. 20 shows the processes until the signal FCH isgenerated. In FIG. 20, by combining the signal CFH, signal ZONE, andedge signal, the edge in a white background can be discriminated fromthat in a dot pattern/halftone image, and black character processing canbe done without emphasizing the dot pattern component even in a dotpattern image or without processing a portion such as a picture edgewhich does not require any black character processing.

[0160] <Operation of LUT 111 Shown in FIG. 3>

[0161] As shown in FIG. 3, the signals edge, col, and zone respectivelydetected, determined, and discriminated by the edge detector 108,saturation determination unit 109, and thickness discrimination circuit110 output a signal sen in accordance with the LUT 111. The feature ofthis LUT 111 is to change the printer resolution for only the edgeportion of the thinnest character.

[0162] <Operation of Smoothing Circuit 104 Shown in FIG. 3>

[0163] The operation of the smoothing circuit 104 shown in FIG. 3 willbe explained below.

[0164]FIG. 21 shows the detailed arrangement of the smoothing circuit104 shown in FIG. 3. In FIG. 21, C, M, Y, and K color component signalsare frame-sequentially transferred as an image signal, and the followingprocessing is done in units of color components. A binarization circuit1001 binarizes the input signal for the next pattern matching. A patternmatching circuit 1002 performs pattern matching based on the binarysignal. A smoothing processing circuit 1003 smoothes staircasingpatterns using data with a resolution twice the original resolution.Note that the data to be substituted by interpolation is determined bychecking the density data of surrounding pixels.

[0165]FIG. 22 shows an example of the actually input image signal, andFIG. 23 shows the smoothing result of the image signal shown in FIG. 22.Note that the area to be smoothed is the thinnest edge portion detectedbased on the image area separation result.

[0166] The detailed arrangements of the circuits show in FIG. 21 will beexplained below. As shown in FIG. 21, the binarization circuit 1001binarizes by extracting bit ORs of the input multi-valued image using anOR gate (not shown). As shown in FIG. 24, in the pattern matchingcircuit 1002, upon reception of image data having a resolution of 400dpi in synchronism with image clocks CLK, the image data is stored inline memories 1 to 9, and at the same time, shift registers 11 to 19pick up dot matrix data of 11 dots (main scanning direction)×9 dots(sub-scanning direction) from dot data in line memories 1 to 9. Afterthat, a determination circuit 1301 detects the feature of that dotmatrix data. Various pattern matching methods have been proposed, andthis embodiment uses such methods. Hence, a detailed description ofpattern matching will be omitted.

[0167] The smoothing circuit 1003 will be explained below. FIG. 25 is aview for explaining an example of smoothing rasterized density data 255in a line having one pixel width. As shown in FIG. 25, the interpolationamount of image data is replaced by multi-valued data in correspondencewith the input pattern. Furthermore, since the input image signal isdata having multi-valued gradation characteristics, it is not alwaysdata 0 or 255. Hence, as shown in FIG. 26, the multi-valued pattern ofthe input image signal is checked using a 3×3 window. That is, thenumber of data other than 0 is counted within the 3×3 window, and theaverage value of the data other than 0 is calculated to obtain data tobe smoothed by a linear calculation, thus attaining data interpolation.A data interpolation example will be explained below.

[0168] According to FIG. 26, the number of data other than 0 in the 3×3window is 3. That is, if the density data of these pixels is 51, wehave:

(51×3)/3=51  (6)

180×51/255=60  (7)

[0169] Hence, if the value to be substituted in FIG. 25 is 180 inequation (7), data “60” is consequently obtained by interpolation incorrespondence with the pattern from equation (7).

[0170] To restate, according to the first embodiment, even when a rasterimage from the external equipment or the image read by the image scannermodule 201 is input in units of Y, M, C, and K color components, densityinterpolation is executed in correspondence with every image patterns ofcharacters, lines, and the like, thus allowing smoother smoothing andimproving the quality of characters and figures.

[0171] Since a multi-color, multi-valued image is smoothed in units ofcolor components, staircasing of color characters and line images evenin a gradation image can be eliminated, thus improving the imagequality.

[0172] [Second Embodiment]

[0173] An image processing system of the second embodiment will beexplained below.

[0174]FIG. 27 is a block diagram showing an image processing system ofthe second embodiment.

[0175] In FIG. 27, reference numerals 1310 to 1315, 1318, and 1319denote the same parts as those in FIG. 32 above, and a detaileddescription thereof will be omitted.

[0176] In FIG. 27, the characteristic feature of the second embodimentlies in that an attribute map memory 1316 is added to a raster imageprocessor 1313, and an image processor 1317 is added to a color printer1318.

[0177] A rasterizer 1314 generates attribute map information by a methodto be described later on the basis of object attributes and thegenerated bitmap image upon generating the bitmap image on an imagememory 1315 on the basis of commands corresponding to individual objectsthat form an image. More specifically, the rasterizer 1314 generatesattribute map information on the basis of attributes of commands thatrepresent the objects, and the bitmap image generated to be written inthe image memory 1315. Note that the contents on the image memory 1315,that have already been mapped to a bitmap image can be referred to. Theimage processor 1317 of the color printer 1318 performs various kinds ofimage processing for the bitmap image on the image memory 1315, andoutputs bitmap data to an image forming unit 1319. Also, the imageprocessor 1317 appropriately switches the image processing method withreference to attribute information on the attribute map memory 1316.

[0178] The method of generating attribute information will be describedin detail below.

[0179]FIG. 28 shows image data mapped on the image memory 1315 in FIG.27. FIGS. 29A to 29E are enlarged views of portion A in FIG. 28, i.e.,showing the method of generating a bitmap image on the basis of acommand for drawing a circular image. FIGS. 30A to 30E are enlargedviews of portion B in FIG. 28.

[0180]FIG. 29A shows bitmap data to be written in the image memory 1315;pixel values in units of micro-pixels are two-dimensionally arranged as,e.g., 8-bit integer values.

[0181]FIGS. 29B to 29E show attribute information to be written in theattribute map memory 1316. For example, four different attributeinformation flags, i.e., vector, character, edge, and edge boundaryflags are generated in units of bits (binary data “0” or “1”) in thesame pixel matrix as that of the bitmap data on the image memory 1315.

[0182] In FIG. 29A, 0 represents a white micro-rectangle, and 1represents a black micro-rectangle. In FIG. 29B, a vector flag is set at“1” in a vector image area such as a character, graphic, or the like,and is set at “0” in other areas, e.g., a background portion andcontinuous gradation picture portion (see portion C in FIG. 28). Hence,all the vector flags inside the circular image in FIG. 29B are set at“1”. The vector flag shown in FIG. 29B can be normally generated on thebasis of a command for drawing a circle. Also, since this embodimentrefers to the contents of FIG. 29A, a new painted area can be detectedto obtain vector flags “1” in FIG. 29B in that area.

[0183] A character flag shown in FIG. 29C is set at “1” in a characterarea, and is set at “0” in other areas. Since the circle is not acharacter, all character flags are set at “0”. An edge flag shown inFIG. 29D is set at “1” at the boundary portion of a circular object.

[0184] An edge flag is set at “1” at the position of the pixel, thevector flag of which is detected to change from “0” to “1”. An edgeboundary flag in FIG. 29E is set at “1” at a pixel position thatneighbors the edge flag.

[0185] The edge boundary flag is generated at both the inside andoutside an edge, as shown in FIG. 29E, by detecting four neighboringpixels of a pixel, the edge flag of which is “1”, and setting “1” atthose pixel positions.

[0186] On the other hand, in some cases, only pixels outside an edge arepreferably set at “1” depending on the image processing contents. Insuch case, edge boundary flags are inhibited from being generated on thehalftone portion (an area indicated black) inside the circle byreferring to the original image memory simultaneously with the edgeflags shown in FIG. 29D.

[0187]FIGS. 30A to 30E show a case wherein attribute map information isgenerated for a character object.

[0188] The meanings of FIGS. 30A to 30E are the same as those of FIGS.29A to 29E, and the types of attribute information generated aresubstantially the same as those in FIGS. 29B to 29E, except for acharacter flag in FIG. 30C. This is because the target image is acharacter object, and character flags inside the entire character areset at “1”.

[0189] The attribute map information is generated in the above-mentionedprocedure. In the continuous gradation image area shown in FIGS. 29A to30E and a background area where no image is drawn, all the flags are setat “0”.

[0190] The bitmap image data on the image memory 1315 and attributeinformation on the attribute map memory 1316 are transferred to theimage processor 1317 together with sync signals (not shown). At thistime, a bitmap image corresponding to a predetermined pixel position onthe image memory 1315, and attribute information of that pixel aretransferred in correspondence with each other. That is, when the pixelvalue of a specific pixel in the image memory 1315 is transferred to theimage processor 1317, attribute information (flag data) of that pixel isnearly simultaneously transferred.

[0191] The image processor 1317 shown in FIG. 27 will be describedbelow.

[0192]FIG. 31 is a block diagram of the image processor 1317 shown inFIG. 27.

[0193] In FIG. 31, image signals Y, M, C, and K according to theabove-mentioned bitmap data output from an external equipment 101 aresequentially transferred in units of scanning frames in a printer unit106, and a density-luminance converter 102 converts density signals Y,M, C, and K into luminance signals R, G, and B using a look-up table ROMin units of colors.

[0194] A luminance-density converter 103 converts three primary colorsignals R, G, and B transferred from the density-luminance converter 102into density signals Y, M, C, and K, and frame-sequentially outputs thedensity signals to have a predetermined bit width (8 bits).

[0195] A smoothing circuit 104 generates data having a resolution twicethe reading resolution in accordance with a 400/800-line switchingsignal (sen signal) as a result of an image area separation unit 107, asin the first embodiment. A γ table 105 converts the resolution-converteddensity data in correspondence with the gradation reproductioncharacteristics of the printer. The processed image signals M, C, Y, andK and the sen signal serving as a 400/800-line switching signal are sentto the laser driver, and the printer unit 106 performs density recordingby PWM.

[0196] The image area separation unit 107 has an edge detector 108,thickness discrimination circuit 110, and look-up table (LUT) 111. Theedge detector 108 generates an edge signal edge from image signals R, G,and B output from the density-luminance converter 102, and outputs it tothe LUT 111. The thickness discrimination circuit 110 generates athickness signal zone from image signals R, G, and B output from thedensity-luminance converter 102, and outputs it to the LUT 111.

[0197] <Operation of LUT 111 Shown in FIG. 31>

[0198] The operation of the LUT 111 shown in FIG. 31 will be explainedbelow.

[0199] As shown in FIG. 31, the LUT 111 outputs a sen signal inaccordance with the signals edge and zone output from the edge detector108 and thickness discrimination circuit 110, and attribute informationoutput from the external equipment 101, and the printer can performappropriate processing in accordance with the types of objects of a PDLimage.

[0200] The features of the LUT 111 are:

[0201] Multi-valued black character processing can be made incorrespondence with the thickness of a character (for example, in caseof a thick character, an 800-line signal is used near an edge ascompared to the interior of a character, so as to further emphasize theedge, i.e., the character).

[0202] Since a plurality of edge area ranges are prepared, a blackcharacter processing area (i.e., an area for which an 800- or 400-linesignal is used) can be selected in correspondence with the thickness ofa character.

[0203] A character in a dot pattern/halftone image can be processeddifferently from that on a white background.

[0204] The printer resolution is changed only for the thinnest character(e.g., the number of lines increases for thin characters to increase theresolution).

[0205] Of course, in addition to the above-mentioned processing, variouscombinations of processing can be done for the input signal.

[0206] Since the operations of the edge detector 108 and thicknessdiscrimination circuit 110 are the same as those in FIG. 3, a detaileddescription thereof will be omitted.

[0207] To recapitulate, according to the second embodiment, adaptiveprocessing is executed for bitmap data which is generated from commandsrepresenting an image using the attributes of objects that form theimage, and the features of bitmap data, so as to reduce determinationerrors produced when adaptive processing is made using only the featuresof bitmap data. Furthermore, upon improving the image quality, since thenumber of lines upon interpolation, smoothing, and image formation iscontrolled, staircasing at the edge portion of, e.g., a characterobject, can be reduced, and a high-resolution image can be provided.

[0208] [Third Embodiment]

[0209]FIG. 33 is a timing chart showing the control for densityreproduction of a printer according to the second embodiment.

[0210] In FIG. 33, a signal S1 is a printer pixel clock signalcorresponding to a resolution of 400 dpi. The printer pixel clock signalS1 is generated by the laser driver 212. A 400-line triangular wave S2is generated in synchronism with the printer pixel clock signal S1. Theperiod of the 400-line triangular wave S2 is the same as that of theprinter pixel clock signal S1.

[0211] 256-gradation (8-bit) M, C, Y, and BK image data transferred fromthe image processing unit 209 shown in FIG. 1, and a line numberswitching signal S8 for switching 400 lines/800 lines are synchronizedwith the printer pixel clock signal S1 by a FIFO memory (not shown) inthe laser driver 212, and are transferred in synchronism with theprinter pixel clock signal S1.

[0212] 8-bit digital image data is converted into an analog image signalS3 by a D/A converter. The analog image signal S3 is compared with theabove-mentioned 400-line triangular wave S2 in an analog manner togenerate a 400-line PWM output S4. More specifically, the 400-linetriangular wave S2 modulates the pulse width of the analog image signalS3 at a resolution of 400 dpi.

[0213] Digital pixel data changes from 00H to FFH, and the 400-line PWMoutput S4 has a pulse width corresponding to this value. One period ofthe 400-line PWM output S4 is 63.5 μm on the photosensitive drum.

[0214] The laser driver 212 generates an 800-line triangular wave S6having a period twice that of the printer pixel clock signal S1 insynchronism with the signal S1, in addition to the 400-line triangularwave S2.

[0215] Then, an 800-line PWM output signal S7 is generated by comparingthe 800-line triangular wave S6 and 400-dpi analog image signal S3. Thatis, the 800-line triangular wave S6 modulates the pulse width of theanalog image signal S3 at a resolution of 800 dpi.

[0216] The resolution other than 400 and 800 dpi can be set, and in suchcase, the period of the triangular wave is changed appropriately.

[0217] The 800-line PWM output signal S7 forms a latent image on thephotosensitive drum at a period of 31.75 μm, as shown in FIG. 33.

[0218] Upon comparing 800-line density reproduction with 400-linedensity reproduction, 800-line density reproduction that reproducesdensity in units of 31.75 μm is more suitable for recordinghigh-resolution images than 400-line density reproduction thatreproduces density in units of 63.5 μm. On the other hand, 400-linedensity reproduction is suitable for recording an image that places animportance on gradation.

[0219] As described above, recording by the 400-line PWM output signalS4 is suitable for gradation reproduction, and recording by the 800-linePWM output signal S7 is excellent in terms of resolution. For thisreason, the 400- and 800-line PWM output signals S4 and S7 areappropriately selectively output in correspondence with the features ofimage data such as characters, figures, and the like.

[0220] When the line number switching signal S8 is Low level, the800-line PWM output signal S7 is selected; when it is High level, the400-line PWM output signal S4 is selected.

[0221] [Circuit Arrangement]

[0222] The control circuit arrangement for density reproduction of theprinter will be explained below with reference to FIG. 34 FIG. 34 showsthe control circuit arrangement for density reproduction of the printer.

[0223] In FIG. 34, a bitmap image signal output from an externalequipment 101 such as a personal computer is subjected to patternmatching in a pattern matching circuit 102. When the input image signalmatches a given pattern in the pattern matching circuit 102, “0” isoutput as the line number switching signal S8 shown in FIG. 33; when theinput image signal does not have a matching pattern, “1” is output. Asmoothing processing circuit 103 smoothes staircasing patterns usingdata with a resolution twice the original resolution. Note that the datato be substituted by interpolation is determined by checking the densitydata of surrounding pixels. A PWM control circuit 104 switches theresolution in correspondence with the line number switching signal S8.

[0224]FIG. 22 shows an example of the actually input image signal, andFIG. 23 shows the smoothing result of the image signal shown in FIG. 22.Note that the portion to be smoothed is only an edge portion detectedbased on the image area separation result.

[0225] The detailed arrangements of the circuits shown in FIG. 34 willbe described below.

[0226] In the pattern matching circuit 102 shown in FIG. 34, as shown inFIG. 24, upon reception of image data having a resolution of 400 dpi insynchronism with image clocks CLK, the image data is stored in linememories 1 to 9, and at the same time, shift registers 11 to 19 pick updot matrix data of 11 dots (main scanning direction)×9 dots(sub-scanning direction) from dot data in line memories 1 to 9. Afterthat, a determination circuit 1301 detects the feature of that dotmatrix data. Various pattern matching methods have been proposed, andthis embodiment uses such methods. Hence, a detailed description ofpattern matching will be omitted.

[0227]FIGS. 35A and 35B are views for explaining the algorithm forextracting the feature of a dot pattern over the entire matrix area of11 dots (main scanning direction)×9 dots (sub-scanning direction) anddiscriminating whether or not the dot pattern is to be smoothed.

[0228]FIG. 35A shows a reference area of 11 dots (main scanningdirection)×9 dots (sub-scanning direction), and expresses 99 pixels in amatrix of a, b, c, d, e, f, g, h, i, j, and k in the main scanningdirection, and 1, 2, 3, 4, 5, 6, 7, 8, and 9 in the sub-scanningdirection. For example, the central pixel is expressed by “5 f”. FIG.35B shows the state wherein thereference area shown in FIG. 35A isdivided into 17 groups X1 to X8, Y1 to Y8, and 5 f. In FIG. 35B, thecentral pixel 5 f is selected as the pixel to be changed for smoothing.

[0229] In FIG. 35B, the groups are similarly formed so that group X1includes pixels 3 d, 3 e, 3 f, 4 d, 4 e, and 4 f, group X2 includespixels 3 f, 3 g, 3 h, 4 f, 4 g, and 4 h, group X3 includes pixels 6 d, 6e, 6 f, 7 d, 7 e, and 7 f, and so forth. These groups can be classifiedinto eight groups (X1 to X8) consisting of six dots, six groups (Y1, Y3to Y5, Y7, and Y8) consisting of nine dots, two groups (Y2 andY6)consisting of 10 dots, and the central pixel 5 f.

[0230] Note that the feature of each group is expressed by Xn or Yn.When all dots in a certain group are the same, the feature of that groupis represented by “0”. On the other hand, when dots in a certain groupare different from each other, the feature of that group is representedby “1”. With this procedure, features X1 to X8 and Y1 to Y8 of thegroups are obtained. Based on the obtained pattern matching result, thesmoothing processing circuit 103 two-divisionally substitutes apredetermined density for a predetermined pattern.

[0231] The smoothing processing circuit 103 will be explained below.

[0232] As shown in FIG. 25, the interpolation amount of image data isreplaced by multi-valued data in correspondence with the input pattern.Furthermore, since the input image signal is data having multi-valuedgradation characteristics, it is not always data 0 or 255.1318 Hence, asshown in FIG. 26, the multi-valued pattern of the input image signal ischecked using a 3×3 window. That is, the number of data other than 0 iscounted within the 3×3 window, and the average value of the data otherthan 0 is calculated to obtain data to be smoothed by a linearcalculation, thus attaining data interpolation. A data interpolationexample will be explained below.

[0233] According to FIG. 26, the number of data other than 0 in the 3×3window is 3. That is, if the density data of these pixels is 51, we haveequations (6) and (7) above. Hence, if the value to be substituted inFIG. 25 is 180 in equation (7), data “60” is consequently obtained uponinterpolation in correspondence with the pattern from equation (7).

[0234] To restate, according to the third embodiment, even when a rasterimage is input from the external equipment in units of Y, M, C, and Kcolor components, density interpolation is executed in correspondencewith every image patterns of characters, lines, and the like, thusallowing smoother smoothing and improving the quality of characters andfigures.

[0235] As described above, according to the third embodiment, when imagedata such as a character or the like which places an importance onresolution is to be processed, the edge of the character or the like canbe smoothed to increase resolution. On the other hand, when image datawhich places an importance on gradation characteristics is to beprocessed, it can be directly output without increasing the resolution.

[0236] [Fourth Embodiment]

[0237] In the first to third embodiments, when it is determined as aresult of pattern matching corresponding to the image characteristicsthat the resolution is to be converted, density interpolation isimplemented at a resolution having a larger value (e.g., twice) thereading resolution. In order to further increase the resolution and toremove staircasing, data maybe interpolated at a resolution N times (Nis a natural number) the reading resolution.

[0238] [Other Embodiments]

[0239] Note that the present invention may be applied to either a systemconstituted by a plurality of equipments (e.g., a host computer, aninterface device, a reader, a printer, and the like), or an apparatusconsisting of a single equipment (e.g., a copying machine, a facsimileapparatus, or the like).

[0240] The objects of the present invention are also achieved bysupplying a storage medium, which records a program code of a softwareprogram that can realize the functions of the above-mentionedembodiments to the system or apparatus, and reading out and executingthe program code stored in the storage medium by a computer (or a CPU orMPU) of the system or apparatus.

[0241] In this case, the program code itself read out from the storagemedium realizes the functions of the above-mentioned embodiments, andthe storage medium which stores the program code constitutes the presentinvention.

[0242] As the storage medium for supplying the program code, forexample, a floppy disk, hard disk, optical disk, magneto-optical disk,CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, and the likemay be used.

[0243] The functions of the above-mentioned embodiments may be realizednot only by executing the readout program code by the computer but alsoby some or all of actual processing operations executed by an OS(operating system) running on the computer on the basis of aninstruction of the program code.

[0244] Furthermore, the functions of the above-mentioned embodiments maybe realized by some or all of actual processing operations executed by aCPU or the like arranged in a function extension board or a functionextension unit, which is inserted in or connected to the computer, afterthe program code read out from the storage medium is written in a memoryof the extension board or unit.

[0245] When the present invention is applied to the storage medium, thestorage medium stores program codes corresponding to the above-mentionedflow chart. In this case, modules shown in memory map examples in FIGS.36 to 38 are stored in the storage medium.

[0246] That is, program codes of at least an “input step module”, a“detection step module”, and a “smoothing step module” can be stored inthe storage medium.

[0247] Also, program codes of at least an “input step module”, a “bitmapdata generation step module”, and an “attribute generation step module”can be stored in the storage medium.

[0248] Furthermore, program codes of at least an “input step module”, a“detection step module”, a “smoothing step module”, an “output stepmodule”, and a “switching step module” can be stored in the storagemedium.

[0249] As many apparently widely different embodiments of the presentinvention can be made without departing from the spirit and scopethereof, it is to be understood that the invention is not limited to thespecific embodiments thereof except as defined in the appended claims.

What is claimed is:
 1. An image processing apparatus characterized bycomprising: input means for inputting multi-valued image data having aplurality of color components; detection means for detecting an area tobe smoothed from the multi-valued image data having the plurality ofcolor components; and smoothing means for smoothing multi-valued imagedata included in the area detected by said detection means in units ofcolor components.
 2. The apparatus according to claim 1, characterizedin that said smoothing means further comprises resolution conversionmeans for generating image data having a resolution twice a resolutionof the multi-valued image data having the plurality of color componentsfrom the multi-valued image data in the area detected by said detectionmeans.
 3. The apparatus according to claim 2, characterized in that saidresolution conversion means generates image data having a resolutioncorresponding to a natural number multiple of the resolution of themulti-valued image data having the plurality of color components fromthe multi-valued image data in the area detected by said detectionmeans.
 4. The apparatus according to claim 1, characterized in that themulti-valued image data having the plurality of color components isfull-color image data which is color-separated into yellow, magenta,cyan, and black components.
 5. The apparatus according to claim 1,characterized in that the multi-valued image data having the pluralityof color components is input from external equipment.
 6. The apparatusaccording to claim 1, characterized by further comprising means fordetermining a thickness of character and line image portions in anoriginal image, means for determining an edge of a character or lineimage in the original image, and means for determining saturation of theline image in the original image.
 7. The apparatus according to claim 2,characterized in that said resolution conversion means generates imagedata having a resolution twice the resolution of the multi-valued imagedata having the plurality of color components by interpolating theresolution of the multi-valued image data.
 8. The apparatus according toclaim 3, characterized in that said resolution conversion meansgenerates image data having a resolution corresponding to the naturalnumber multiple of the resolution of the multi-valued image data havingthe plurality of color components by interpolating the resolution of themulti-valued image data.
 9. An image processing method characterized bycomprising: the input step of inputting multi-valued image data having aplurality of color components; the detection step of detecting an areato be smoothed from the multi-valued image data having the plurality ofcolor components; and the smoothing step of smoothing multi-valued imagedata included in the area detected in the detection step in units ofcolor components.
 10. The method according to claim 9, characterized inthat the smoothing step further comprises the resolution conversion stepof generating image data having a resolution twice a resolution of themulti-valued image data having the plurality of color components fromthe multi-valued image data in the area detected in the detection step.11. The method according to claim 10, characterized in that theresolution conversion step includes the step of generating image datahaving a resolution corresponding to a natural number multiple of theresolution of the multi-valued image data having the plurality of colorcomponents from the multi-valued image data in the area detected in thedetection step.
 12. The method according to claim 9, characterized inthat the multi-valued image data having the plurality of colorcomponents is full-color image data which is color-separated intoyellow, magenta, cyan, and black components.
 13. The method according toclaim 9, characterized in that the multi-valued image data having theplurality of color components is input from external equipment.
 14. Themethod according to claim 9, characterized by further comprising thestep of determining a thickness of character and line image portions inan original image, the step of determining an edge of a character orline image in the original image, and the step of determining saturationof the line image in the original image.
 15. The method according toclaim 10, characterized in that the resolution conversion step includesthe step of generating image data having a resolution twice theresolution of the multi-valued image data having the plurality of colorcomponents by interpolating the resolution of the multi-valued imagedata.
 16. The method according to claim 11, characterized in that theresolution conversion step includes the step of generating image datahaving a resolution corresponding to the natural number multiple of theresolution of the multi-valued image data having the plurality of colorcomponents by interpolating the resolution of the multi-valued imagedata.
 17. A computer-readable memory which stores a program code ofimage processing, characterized by comprising: a code of the input stepof inputting multi-valued image data having a plurality of colorcomponents; a code of the detection step of detecting an area to besmoothed from the multi-valued image data having the plurality of colorcomponents; and a code of the smoothing step of smoothing multi-valuedimage data included in the area detected in the detection step in unitsof color components.
 18. An image processing apparatus characterized bycomprising: input means for inputting a command that represents animage; bitmap data generation means for generating bitmap data on thebasis of the command that represents the image; and attribute generationmeans for generating attribute information on the basis of an attributeof an object that forms an image, and the bitmap data.
 19. The apparatusaccording to claim 18, characterized in that the attribute informationis generated in correspondence with a two-dimensional coordinateposition of the bitmap data, and attribute information at an identicalcoordinate position with the bitmap data is output in synchronism withthe bitmap data.
 20. The apparatus according to claim 18, characterizedby further comprising switching means for switching the number of outputlines in correspondence with a thickness of a character/line image inthe image.
 21. The apparatus according to claim 18, characterized inthat the bitmap data is full-color image data which is color-separatedinto yellow, magenta, cyan, and black components.
 22. The apparatusaccording to claim 18, characterized by further comprising means fordetermining a thickness of character and line image portions in theimage, means for determining an edge of a character or line image in theimage, and means for determining saturation of the line image in theimage.
 23. The apparatus according to claim 18, characterized by furthercomprising means for generating resolution-improved image data byinterpolating a resolution of the bitmap data in accordance with theattribute information.
 24. The apparatus according to claim 18,characterized in that the attribute information includes one ofinformation indicating whether data of interest is a vector image areaor not, information indicating whether the data of interest is acharacter area or not, information indicating whether the data ofinterest is an object boundary portion or not, information of a pixelwhere the vector image area changes, and information of a pixel whichneighbors the pixel where the vector image area changes.
 25. Theapparatus according to claim 18, characterized in that the bitmap datais smoothed in accordance with the attribute information.
 26. Theapparatus according to claim 18, characterized in that the number oflines used in image formation is determined and the bitmap data issmoothed in accordance with the attribute information.
 27. An imageprocessing method characterized by comprising: the input step ofinputting a command that represents an image; the bitmap data generationstep of generating bitmap data on the basis of the command thatrepresents the image; and the attribute generation step of generatingattribute information on the basis of an attribute of an object thatforms an image, and the bitmap data.
 28. The method according to claim27, characterized in that the attribute information is generated incorrespondence with a two-dimensional coordinate position of the bitmapdata, and attribute information at an identical coordinate position withthe bitmap data is output in synchronism with the bitmap data.
 29. Themethod according to claim 27, characterized by further comprising theswitching step of switching the number of output lines in correspondencewith a thickness of a character/line image in the image.
 30. The methodaccording to claim 27, characterized in that the bitmap data isfull-color image data which is color-separated into yellow, magenta,cyan, and black components.
 31. The method according to claim 27,characterized by further comprising the step of determining a thicknessof character and line image portions in the image, the step ofdetermining an edge of a character or line image in the image, and thestep of determining saturation of the line image in the image.
 32. Themethod according to claim 27, characterized by further comprising thestep of generating resolution-improved image data by interpolating aresolution of the bitmap data in accordance with the attributeinformation.
 33. The method according to claim 27, characterized in thatthe attribute information includes one of information indicating whetherdata of interest is a vector image area or not, information indicatingwhether the data of interest is a character area or not, informationindicating whether the data of interest is an object boundary portion ornot, information of a pixel where the vector image area changes, andinformation of a pixel which neighbors the pixel where the vector imagearea changes.
 34. The method according to claim 27, characterized inthat the bitmap data is smoothed in accordance with the attributeinformation.
 35. The method according to claim 27, characterized in thatthe number of lines used in image formation is determined and the bitmapdata is smoothed in accordance with the attribute information.
 36. Acomputer-readable memory which stores a program code of imageprocessing, characterized by comprising: a code of the input step ofinputting a command that represents an image; a code of the bitmap datageneration step of generating bitmap data on the basis of the commandthat represents the image; and a code of the attribute generation stepof generating attribute information on the basis of an attribute of anobject that forms an image, and the bitmap data.
 37. An image processingapparatus characterized by comprising: input means for inputting imagedata having a plurality of color components, obtained bycolor-separating an image; detection means for detecting an area to besmoothed from the image data having the plurality of color components;smoothing means for smoothing the image data having the plurality ofcolor components included in the area detected by said detection means;output means for outputting a recording signal of a predeterminedresolution on the basis of the smoothed image data; and switching meansfor switching an output resolution of said output means.
 38. Theapparatus according to claim 37, characterized in that said output meansgenerates a recording signal, a pulse width of which is modulated on thebasis of the smoothed image data and a reference signal, and saidswitching means switches the output resolution by switching therecording signal.
 39. The apparatus according to claim 38, characterizedin that said output means modulates the pulse width of the recordingsignal using at least two reference signals having different periods.40. The apparatus according to claim 39, characterized in that saidswitching means selects one of the two reference signals havingdifferent periods.
 41. The apparatus according to claim 37,characterized in that said smoothing means smoothes bitmap image data ata resolution twice a resolution of the image data in the area detectedby said detection means.
 42. The apparatus according to claim 37,characterized in that said smoothing means smoothes bitmap image data ata resolution corresponding to a natural number multiple of a resolutionof the image data in the area detected by said detection means.
 43. Theapparatus according to claim 37, characterized in that the image datahaving the plurality of color components is full-color image data whichis color-separated into yellow, magenta, cyan, and black components. 44.The apparatus according to claim 37, characterized in that the imagedata having the plurality of color components is read from externalequipment.
 45. The apparatus according to claim 41, characterized inthat said smoothing means generates image data having a resolution twicethe resolution of the image data having the plurality of colorcomponents by interpolating the image data.
 46. The apparatus accordingto claim 42, characterized in that said smoothing means generates imagedata having a resolution corresponding to the natural number multiple ofthe resolution of the image data having the plurality of colorcomponents by interpolating the image data.
 47. An image processingmethod characterized by comprising: the input step of inputting imagedata having a plurality of color components, obtained bycolor-separating an image; the detection step of detecting an area to besmoothed from the image data having the plurality of color components;the smoothing step of smoothing the image data having the plurality ofcolor components included in the area detected in the detection step;the output step of outputting a recording signal of a predeterminedresolution on the basis of the smoothed image data; and the switchingstep of switching an output resolution of the output step incorrespondence with a characteristic of the smoothed image data.
 48. Themethod according to claim 47, characterized in that the output stepincludes the step of generating a recording signal, a pulse width ofwhich is modulated on the basis of the smoothed image data and areference signal, and the switching step includes the step of switchingthe output resolution by switching the recording signal.
 49. The methodaccording to claim 48, characterized in that the output step includesthe step of modulating the pulse width of the recording signal using atleast two reference signals having different periods.
 50. The methodaccording to claim 49, characterized in that the switching step includesthe step of selecting one of the two reference signals having differentperiods.
 51. The method according to claim 47, characterized in that theimage data having the plurality of color components is full-color imagedata which is color-separated into yellow, magenta, cyan, and blackcomponents.
 52. The method according to claim 47, characterized in thatthe image data having the plurality of color components is read fromexternal equipment.
 53. A computer-readable memory which stores aprogram code of image processing, characterized by comprising: a code ofthe input step of inputting image data having a plurality of colorcomponents, obtained by color-separating an image; a code of thedetection step of detecting an area to be smoothed from the image datahaving the plurality of color components; a code of the smoothing stepof smoothing the image data having the plurality of color componentsincluded in the area detected in the detection step; a code of theoutput step of outputting a recording signal of a predeterminedresolution on the basis of the smoothed image data; and a code of theswitching step of switching an output resolution of the output step incorrespondence with a characteristic of the smoothed image data.